Silvicultural approaches for management of eastern white pine to minimize impacts of damaging agents
Bibliographic record
Abstract
Summary Since the arrival to North America ofCronartium ribicola, management of eastern white pine has been driven by the need to avoid the actual or, in many areas, the perceived damage caused by white pine blister rust. Although white pine has lost much of its former dominance, it remains a valuable species for biotic diversity, aesthetics, wildlife habitat and forest products. Understanding its silvics and damaging agents provides a sound basis for the silvicultural activities of site selection, regeneration and stand tending. The species can be successfully grown in many locations despite herbivory, competition, white pine weevil and blister rust. Forest managers can minimize damage by applying knowledge of local conditions (climate, soils, physiography and vegetation) to hazard assessment, site selection and preparation, vegetation management, and pruning. With appropriate management and a long‐term commitment, many eastern forests can be beneficially reforested to eastern white pine with little impact from blister rust and other damaging agents.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".